from copy import deepcopy from mmengine.config import read_base with read_base(): # choose a list of datasets from opencompass.configs.datasets.gpqa.gpqa_openai_simple_evals_gen_5aeece import gpqa_datasets # noqa: F401, E501 from opencompass.configs.datasets.IFEval.IFEval_gen_353ae7 import ifeval_datasets # noqa: F401, E501 from opencompass.configs.datasets.math.math_0shot_gen_11c4b5 import math_datasets # noqa: F401, E501 # read hf models - chat models from opencompass.configs.models.chatglm.lmdeploy_glm4_9b_chat import ( models as lmdeploy_glm4_9b_chat_model, # noqa: F401, E501 ) from opencompass.configs.models.deepseek.lmdeploy_deepseek_r1_distill_qwen_32b import ( models as lmdeploy_deepseek_r1_distill_qwen_32b_model, # noqa: F401, E501 ) from opencompass.configs.models.deepseek.lmdeploy_deepseek_v2_5_1210 import ( models as lmdeploy_deepseek_v2_5_1210_model, # noqa: F401, E501 ) from opencompass.configs.models.deepseek.lmdeploy_deepseek_v2_lite import ( models as lmdeploy_deepseek_v2_lite_model, # noqa: F401, E501 ) from opencompass.configs.models.gemma.lmdeploy_gemma_9b_it import ( models as pytorch_gemma_9b_it_model, # noqa: F401, E501 ) from opencompass.configs.models.gemma.lmdeploy_gemma_27b_it import ( models as pytorch_gemma_27b_it_model, # noqa: F401, E501 ) from opencompass.configs.models.hf_internlm.lmdeploy_internlm2_5_7b_chat import ( models as lmdeploy_internlm2_5_7b_chat_model, # noqa: F401, E501 ) from opencompass.configs.models.hf_internlm.lmdeploy_internlm2_5_20b_chat import ( models as lmdeploy_internlm2_5_20b_chat_model, # noqa: F401, E501 ) from opencompass.configs.models.hf_internlm.lmdeploy_internlm2_chat_1_8b import ( models as lmdeploy_internlm2_chat_1_8b_model, # noqa: F401, E501 ) from opencompass.configs.models.hf_internlm.lmdeploy_internlm2_chat_1_8b_sft import ( models as lmdeploy_internlm2_chat_1_8b_sft_model, # noqa: F401, E501 ) from opencompass.configs.models.hf_internlm.lmdeploy_internlm2_chat_7b import ( models as lmdeploy_internlm2_chat_7b_model, # noqa: F401, E501 ) from opencompass.configs.models.hf_internlm.lmdeploy_internlm2_chat_7b_sft import ( models as lmdeploy_internlm2_chat_7b_sft_model, # noqa: F401, E501 ) from opencompass.configs.models.hf_internlm.lmdeploy_internlm3_8b_instruct import ( models as lmdeploy_internlm3_8b_instruct_model, # noqa: F401, E501 ) from opencompass.configs.models.hf_llama.lmdeploy_llama2_7b_chat import ( models as lmdeploy_llama2_7b_chat_model, # noqa: F401, E501 ) from opencompass.configs.models.hf_llama.lmdeploy_llama3_1_8b_instruct import ( models as lmdeploy_llama3_1_8b_instruct_model, # noqa: F401, E501 ) from opencompass.configs.models.hf_llama.lmdeploy_llama3_2_3b_instruct import ( models as lmdeploy_llama3_2_3b_instruct_model, # noqa: F401, E501 ) from opencompass.configs.models.hf_llama.lmdeploy_llama3_3_70b_instruct import ( models as lmdeploy_llama3_3_70b_instruct_model, # noqa: F401, E501 ) from opencompass.configs.models.hf_llama.lmdeploy_llama3_8b_instruct import ( models as lmdeploy_llama3_8b_instruct_model, # noqa: F401, E501 ) from opencompass.configs.models.mistral.lmdeploy_mistral_large_instruct_2411 import ( models as lmdeploy_mistral_large_instruct_2411_model, # noqa: F401, E501 ) from opencompass.configs.models.mistral.lmdeploy_mistral_nemo_instruct_2407 import ( models as lmdeploy_mistral_nemo_instruct_2407_model, # noqa: F401, E501 ) from opencompass.configs.models.mistral.lmdeploy_mistral_small_instruct_2409 import ( models as lmdeploy_mistral_small_instruct_2409_model, # noqa: F401, E501 ) from opencompass.configs.models.nvidia.lmdeploy_nemotron_70b_instruct_hf import ( models as lmdeploy_nemotron_70b_instruct_hf_model, # noqa: F401, E501 ) from opencompass.configs.models.qwen.lmdeploy_qwen2_1_5b_instruct import ( models as lmdeploy_qwen2_1_5b_instruct_model, # noqa: F401, E501 ) from opencompass.configs.models.qwen.lmdeploy_qwen2_7b_instruct import ( models as lmdeploy_qwen2_7b_instruct_model, # noqa: F401, E501 ) from opencompass.configs.models.qwen2_5.lmdeploy_qwen2_5_0_5b_instruct import ( models as lmdeploy_qwen2_5_0_5b_instruct_model, # noqa: F401, E501 ) from opencompass.configs.models.qwen2_5.lmdeploy_qwen2_5_3b_instruct import ( models as lmdeploy_qwen2_5_3b_instruct_model, # noqa: F401, E501 ) from opencompass.configs.models.qwen2_5.lmdeploy_qwen2_5_14b_instruct import ( models as lmdeploy_qwen2_5_14b_instruct_model, # noqa: F401, E501 ) from opencompass.configs.models.qwen2_5.lmdeploy_qwen2_5_32b_instruct import ( models as lmdeploy_qwen2_5_32b_instruct_model, # noqa: F401, E501 ) from opencompass.configs.models.qwen2_5.lmdeploy_qwen2_5_72b_instruct import ( models as lmdeploy_qwen2_5_72b_instruct_model, # noqa: F401, E501 ) from opencompass.configs.models.yi.lmdeploy_yi_1_5_6b_chat import ( models as lmdeploy_yi_1_5_6b_chat_model, # noqa: F401, E501 ) from opencompass.configs.models.yi.lmdeploy_yi_1_5_9b_chat import ( models as lmdeploy_yi_1_5_9b_chat_model, # noqa: F401, E501 ) from opencompass.configs.models.yi.lmdeploy_yi_1_5_34b_chat import ( models as lmdeploy_yi_1_5_34b_chat_model, # noqa: F401, E501 ) from .volc import infer as volc_infer # noqa: F401, E501 datasets = sum([v for k, v in locals().items() if k.endswith('_datasets')], []) pytorch_glm4_9b_chat_model = deepcopy(lmdeploy_glm4_9b_chat_model) pytorch_deepseek_v2_lite_model = deepcopy(lmdeploy_deepseek_v2_lite_model) pytorch_deepseek_v2_5_1210_model = deepcopy(lmdeploy_deepseek_v2_5_1210_model) pytorch_internlm3_8b_instruct_model = deepcopy(lmdeploy_internlm3_8b_instruct_model) pytorch_internlm2_5_7b_chat_model = deepcopy(lmdeploy_internlm2_5_7b_chat_model) pytorch_internlm2_5_20b_chat_model = deepcopy(lmdeploy_internlm2_5_20b_chat_model) pytorch_llama3_2_3b_instruct_model = deepcopy(lmdeploy_llama3_2_3b_instruct_model) pytorch_llama3_3_70b_instruct_model = deepcopy(lmdeploy_llama3_3_70b_instruct_model) pytorch_mistral_nemo_instruct_2407_model = deepcopy(lmdeploy_mistral_nemo_instruct_2407_model) pytorch_mistral_small_instruct_2409_model = deepcopy(lmdeploy_mistral_small_instruct_2409_model) pytorch_qwen2_5_72b_instruct_model = deepcopy(lmdeploy_qwen2_5_72b_instruct_model) pytorch_qwen2_5_32b_instruct_model = deepcopy(lmdeploy_qwen2_5_32b_instruct_model) pytorch_qwen2_7b_instruct_model = deepcopy(lmdeploy_qwen2_7b_instruct_model) pytorch_yi_1_5_34b_chat_model = deepcopy(lmdeploy_yi_1_5_34b_chat_model) pytorch_deepseek_v2_5_1210_model['engine_config']['cache_max_entry_count'] = 0.6 lmdeploy_glm4_9b_chat_model_native = deepcopy(lmdeploy_glm4_9b_chat_model) lmdeploy_deepseek_r1_distill_qwen_32b_model_native = deepcopy(lmdeploy_deepseek_r1_distill_qwen_32b_model) lmdeploy_deepseek_v2_lite_model_native = deepcopy(lmdeploy_deepseek_v2_lite_model) lmdeploy_deepseek_v2_5_1210_model_native = deepcopy(lmdeploy_deepseek_v2_5_1210_model) lmdeploy_internlm3_8b_instruct_model_native = deepcopy(lmdeploy_internlm3_8b_instruct_model) lmdeploy_internlm2_5_7b_chat_model_native = deepcopy(lmdeploy_internlm2_5_7b_chat_model) lmdeploy_internlm2_5_20b_chat_model_native = deepcopy(lmdeploy_internlm2_5_20b_chat_model) lmdeploy_llama3_1_8b_instruct_model_native = deepcopy(lmdeploy_llama3_1_8b_instruct_model) lmdeploy_llama3_2_3b_instruct_model_native = deepcopy(lmdeploy_llama3_2_3b_instruct_model) lmdeploy_llama3_8b_instruct_model_native = deepcopy(lmdeploy_llama3_8b_instruct_model) lmdeploy_llama3_3_70b_instruct_model_native = deepcopy(lmdeploy_llama3_3_70b_instruct_model) lmdeploy_mistral_large_instruct_2411_model_native = deepcopy(lmdeploy_mistral_large_instruct_2411_model) lmdeploy_mistral_nemo_instruct_2407_model_native = deepcopy(lmdeploy_mistral_nemo_instruct_2407_model) lmdeploy_mistral_small_instruct_2409_model_native = deepcopy(lmdeploy_mistral_small_instruct_2409_model) lmdeploy_nemotron_70b_instruct_hf_model_native = deepcopy(lmdeploy_nemotron_70b_instruct_hf_model) lmdeploy_qwen2_5_0_5b_instruct_model_native = deepcopy(lmdeploy_qwen2_5_0_5b_instruct_model) lmdeploy_qwen2_5_14b_instruct_model_native = deepcopy(lmdeploy_qwen2_5_14b_instruct_model) lmdeploy_qwen2_5_32b_instruct_model_native = deepcopy(lmdeploy_qwen2_5_32b_instruct_model) lmdeploy_qwen2_5_72b_instruct_model_native = deepcopy(lmdeploy_qwen2_5_72b_instruct_model) lmdeploy_qwen2_7b_instruct_model_native = deepcopy(lmdeploy_qwen2_7b_instruct_model) lmdeploy_yi_1_5_6b_chat_model_native = deepcopy(lmdeploy_yi_1_5_6b_chat_model) lmdeploy_yi_1_5_34b_chat_model_native = deepcopy(lmdeploy_yi_1_5_34b_chat_model) for model in [v for k, v in locals().items() if k.startswith('lmdeploy_') or k.startswith('pytorch_')]: for m in model: m['engine_config']['max_batch_size'] = 512 m['gen_config']['do_sample'] = False m['batch_size'] = 5000 for model in [v for k, v in locals().items() if k.startswith('lmdeploy_')]: for m in model: m['backend'] = 'turbomind' for model in [v for k, v in locals().items() if k.startswith('pytorch_')]: for m in model: m['abbr'] = m['abbr'].replace('turbomind', 'pytorch').replace('lmdeploy', 'pytorch') m['backend'] = 'pytorch' for model in [v for k, v in locals().items() if k.endswith('_native')]: for m in model: m['abbr'] = m['abbr'] + '_native' m['engine_config']['communicator'] = 'native' # models = sum([v for k, v in locals().items() if k.startswith('lmdeploy_') or k.startswith('pytorch_')], []) # models = sorted(models, key=lambda x: x['run_cfg']['num_gpus']) summarizer = dict( dataset_abbrs=[ ['GPQA_diamond', 'accuracy'], ['math', 'accuracy'], ['IFEval', 'Prompt-level-strict-accuracy'], ], summary_groups=sum([v for k, v in locals().items() if k.endswith('_summary_groups')], []), )